MétaCan
Menu
← Back to cohort

Abstract 12580: Impact of Zero Coronary Artery Calcium on Downstream Cardiac Testing

2023· article· en· W4388420278 on OpenAlexaffabout
Ethan Lin, Rea Alonzo, Jiming Fang, Anna Chu, Levi Elhadad, Shalane Basque, Harindra C. Wijeysundera, Kate Hanneman, Elsie T. Nguyen, Michael E. Farkouh, Jacob A. Udell, Idan Roifman

Bibliographic record

VenueCirculation · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity Health NetworkSunnybrook Health Science CentreInstitute for Clinical Evaluative SciencesUniversity of Toronto
Fundersnot available
KeywordsMedicineCardiologyInternal medicineMyocardial infarctionHeart failureCoronary artery diseaseCoronary artery calciumPopulationStress testing (software)Ejection fraction

Abstract

fetched live from OpenAlex

Introduction: While coronary artery calcium scoring (CAC) has emerged as a useful tool for cardiovascular disease (CVD) risk prediction, its impact on downstream resource use remains unclear, especially in those with zero CAC. The purpose of this study was to determine the relationship between zero CAC and downstream use of cardiac procedures. Methods: Consecutive CAC scores from two academic hospitals in Toronto, Canada, from 2011 - 2019, were linked to population-based databases. Subjects with zero calcium without previous CVD were subsequently propensity score-matched with a non-CAC-tested control group for age, sex, CVD risk factors and comorbidities relevant to receipt of testing. Downstream cardiac testing, myocardial infarction (MI), stroke, and congestive heart failure (CHF) hospitalizations were compared between the two groups. Results were analyzed using descriptive statistics and Cox proportional hazards regression models. Results: 4,884 patients (Mean 56.8y, SD 11.3) underwent CAC scoring, of whom 2,709 (55.5%) had zero CAC (Mean 52.9y, SD 10.6, 55.4% women). Compared to those not tested at 90 days, zero CAC subjects had similar graded exercise stress test (GXT) (72 tests vs 60, p = 0.29), stress echocardiography (40 vs 32, p = 0.34) and myocardial perfusion imaging (MPS) (26 vs 37, p = 0.15), but higher cardiac MRI (CMR) (48 vs 7, p < 0.001) use. At 3.4 years, GXT (HR 1.24, 95% CI 1.14 - 1.35), stress echocardiography (HR 1.80, 95% CI 1.59 - 2.05) and CMR (HR 3.40, 95% CI 2.55 - 4.53) use was higher in the zero CAC group, whereas MPS (HR 1.08, 95% CI 0.97 - 1.21) and catheterization (HR 1.14, 95% CI 0.91 - 1.44) were similar and PCI (HR 0.59, 95% CI 0.35 - 0.98) and CABG (HR 0.14, 95% CI 0.03 - 0.61) were lower. There was an approximately 5-fold lower rate of MI (HR 0.22, 95% CI 0.10 - 0.51) in the zero CAC group at 3.4 years and no difference in stroke (HR 0.98, 95% CI 0.46 - 2.05) or CHF hospitalizations (HR 1.15, 95% CI 0.53 - 2.48). Conclusion: Zero CAC was associated with higher use of some non-invasive cardiac testing, similar use of catheterization, and reduced PCI, CABG and AMI when compared to a propensity score-matched control group. The results support the utility of a zero CAC in limiting invasive procedures while maintaining an association with reduced cardiac events.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.323
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueCirculation→Same topicCardiac Imaging and Diagnostics→French-language works237,207→